Determining the Sun's influence on Lateglacial and Holocene climates: a focus on climate response to centennial-scale solar forcing at 2800cal.BP

2008 ◽  
Vol 27 (1-2) ◽  
pp. 175-184 ◽  
Author(s):  
G. Plunkett ◽  
G.T. Swindles
Eos ◽  
2018 ◽  
Vol 99 ◽  
Author(s):  
T. Dudok de Wit ◽  
B. Funke ◽  
M. Haberreiter ◽  
K. Matthes

Several international initiatives are working to stitch together data describing solar forcing of Earth’s climate. Their objective is to improve understanding of climate response to solar variability.


2013 ◽  
Vol 26 (19) ◽  
pp. 7489-7506 ◽  
Author(s):  
Lon Hood ◽  
Semjon Schimanke ◽  
Thomas Spangehl ◽  
Sourabh Bal ◽  
Ulrich Cubasch

Abstract The surface climate response to 11-yr solar forcing during northern winter is first reestimated by applying a multiple linear regression (MLR) statistical model to Hadley Centre sea level pressure (SLP) and sea surface temperature (SST) data over the 1880–2009 period. In addition to a significant positive SLP response in the North Pacific found in previous studies, a positive SST response is obtained across the midlatitude North Pacific. Negative but insignificant SLP responses are obtained in the Arctic. The derived SLP response at zero lag therefore resembles a positive phase of the Arctic Oscillation (AO). Evaluation of the SLP and SST responses as a function of phase lag indicates that the response evolves from a negative AO-like mode a few years before solar maximum to a positive AO-like mode at and following solar maximum. For comparison, a similar MLR analysis is applied to model SLP and SST data from a series of simulations using an atmosphere–ocean general circulation model with a well-resolved stratosphere. The simulations differed only in the assumed solar cycle variation of stratospheric ozone. It is found that the simulation that assumed an ozone variation estimated from satellite data produces solar SLP and SST responses that are most consistent with the observational results, especially during a selected centennial period. In particular, a positive SLP response anomaly is obtained in the northeastern Pacific and a corresponding positive SST response anomaly extends across the midlatitude North Pacific. The model response versus phase lag also evolves from a mainly negative AO-like response before solar maximum to a mainly positive AO response at and following solar maximum.


2020 ◽  
Vol 125 (24) ◽  
Author(s):  
Clara Orbe ◽  
David Rind ◽  
Jeffrey Jonas ◽  
Larissa Nazarenko ◽  
Greg Faluvegi ◽  
...  

2009 ◽  
Vol 71 (12) ◽  
pp. 1309-1321 ◽  
Author(s):  
Jean-Louis Le Mouël ◽  
Elena Blanter ◽  
Mikhail Shnirman ◽  
Vincent Courtillot
Keyword(s):  

Author(s):  
Anna Langstroff ◽  
Marc C. Heuermann ◽  
Andreas Stahl ◽  
Astrid Junker

AbstractRising temperatures and changing precipitation patterns will affect agricultural production substantially, exposing crops to extended and more intense periods of stress. Therefore, breeding of varieties adapted to the constantly changing conditions is pivotal to enable a quantitatively and qualitatively adequate crop production despite the negative effects of climate change. As it is not yet possible to select for adaptation to future climate scenarios in the field, simulations of future conditions in controlled-environment (CE) phenotyping facilities contribute to the understanding of the plant response to special stress conditions and help breeders to select ideal genotypes which cope with future conditions. CE phenotyping facilities enable the collection of traits that are not easy to measure under field conditions and the assessment of a plant‘s phenotype under repeatable, clearly defined environmental conditions using automated, non-invasive, high-throughput methods. However, extrapolation and translation of results obtained under controlled environments to field environments is ambiguous. This review outlines the opportunities and challenges of phenotyping approaches under controlled environments complementary to conventional field trials. It gives an overview on general principles and introduces existing phenotyping facilities that take up the challenge of obtaining reliable and robust phenotypic data on climate response traits to support breeding of climate-adapted crops.


2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Kaoru Tachiiri

AbstractThe transient climate response to cumulative carbon emissions (TCRE) is a key metric in estimating the remaining carbon budget for given temperature targets. However, the TCRE has a small scenario dependence that can be non-negligible for stringent temperature targets. To investigate the parametric correlations and scenario dependence of the TCRE, the present study uses a 512-member ensemble of an Earth system model of intermediate complexity (EMIC) perturbing 11 physical and biogeochemical parameters under scenarios with steady increases of 0.25%, 0.5%, 1%, 2%, or 4% per annum (ppa) in the atmospheric CO2 concentration (pCO2), or an initial increase of 1% followed by an annual decrease of 1% thereafter. Although a small difference of 5% (on average) in the TCRE is observed between the 1-ppa and 0.5-ppa scenarios, a significant scenario dependence is found for the other scenarios, with a tendency toward large values in gradual or decline-after-a-peak scenarios and small values in rapidly increasing scenarios. For all scenarios, correlation analysis indicates a remarkably large correlation between the equilibrium climate sensitivity (ECS) and the relative change in the TCRE, which is attributed to the longer response time of the high ECS model. However, the correlations of the ECS with the TCRE and its scenario dependence for scenarios with large pCO2 increase rates are slightly smaller, and those of biogeochemical parameters such as plant respiration and the overall pCO2–carbon cycle feedback are larger, than in scenarios with gradual increases. The ratio of the TCREs under the overshooting (i.e., 1-ppa decrease after a 1-ppa increase) and 1-ppa increase only scenarios had a clear positive relation with zero-emission commitments. Considering the scenario dependence of the TCRE, the remaining carbon budget for the 1.5 °C target could be reduced by 17 or 22% (before and after considering the unrepresented Earth system feedback) for the most extreme case (i.e., the 67th percentile when using the 0.25-ppa scenario as compared to the 1-ppa increase scenario). A single ensemble EMIC is also used to indicate that, at least for high ECS (high percentile) cases, the scenario dependence of the TCRE should be considered when estimating the remaining carbon budget.


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